Financial institutions, such as banks and credit unions, process checks and other transaction related data. Larger financial institutions may process a significant volume of checks and transaction data. It is possible, given the volume of data, for multiple instances of the same check or transaction to occur. In other words, duplicate copies of an imaged check or transaction can exist. Duplicate checks and transactions can also exist, for example, because of fraud, data processing errors, and printing errors.
If duplicate instances of a check or a transaction exist, the financial institution processes and posts each of the multiple instances. This means that the same check or transaction is paid out more than once. Such multiple payments lead to accounting issues, service problems, customer dissatisfaction, and losses due to fraud. Furthermore, such double payments or postings can be indicative of fraud.
It should be appreciated that duplicate checks and transactions can be legitimate duplicates. For example, checks presented for return, re-presentment, or re-deposit are examples of such cases. Other such instances may exist.
Financial institutions can employ various methods for detection of such duplicate checks and transactions, typically known as duplicate detection methods. These existing methods suffer from various drawbacks. For example, some current methods for duplicate detection are performed manually. Such manual detection methods include an operator comparing current checks and transaction against an historical database. This type of comparison is time consuming and expensive. Further, operators make errors and miss duplicates.
These and other deficiencies exist.